The creators of the open source project vLLM have announced that they transitioned the popular tool into a VC-backed startup, Inferact, raising $150 million in seed funding at an $800 million ...

Google researchers have warned that large language model (LLM) inference is hitting a wall amid fundamental problems with memory and networking problems, not compute. In a paper authored by ...

For the past decade, the spotlight in artificial intelligence has been monopolized by training. The breakthroughs have largely come from massive compute clusters, trillion-parameter models, and the ...

The CNCF is bullish about cloud-native computing working hand in glove with AI. AI inference is the technology that will make hundreds of billions for cloud-native companies. New kinds of AI-first ...

Cybersecurity researchers have uncovered critical remote code execution vulnerabilities impacting major artificial intelligence (AI) inference engines, including those from Meta, Nvidia, Microsoft, ...

Forbes contributors publish independent expert analyses and insights. I write about the economics of AI. When OpenAI’s ChatGPT first exploded onto the scene in late 2022, it sparked a global obsession ...

Inference MAISI unexpected keys error when loading diffusion model weights. #2042 New issue Open cugwu ...

A monthly overview of things you need to know as an architect or aspiring architect. Unlock the full InfoQ experience by logging in! Stay updated with your favorite authors and topics, engage with ...

Over the past several years, the lion’s share of artificial intelligence (AI) investment has poured into training infrastructure—massive clusters designed to crunch through oceans of data, where speed ...

If the hyperscalers are masters of anything, it is driving scale up and driving costs down so that a new type of information technology can be cheap enough so it can be widely deployed. The ...

As frontier models move into production, they're running up against major barriers like power caps, inference latency, and rising token-level costs, exposing the limits of traditional scale-first ...